Supervised Machine Learning Feedforward Backpropagation Models for Predicting Shelf Life of Processed Cheese

Sumit Goyal, Gyanendra Kumar Goyal

Abstract


Feedforward Artificial Neural Network models with single hidden layer were developed for predicting shelf life of processed cheese. The models were trained with 80% of total observations and validated with 20% of the remaining data. Mean Square Error, Root Mean Square Error, Coefficient of Determination and Nash - Sutcliffo Coefficient were used in order to compare the prediction ability of the developed models. From the study, it is concluded that single layer feedforward models are good in predicting shelf life of processed cheese stored at 7-8o C.


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